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#' Unflatten flatfile data.frames
#' Sometimes data is provided in the \code{\link{flatfile}} format, but we really want it in \code{mrds} format (that is, as distance data, observation table, sample table and region table format). This function undoes the flattening, assuming that the data have the correct columns.
#' @param data data in flatfile format (a \code{data.frame})
#' @return \code{list} of four \code{data.frame}s: distance data, observation table, sample table, region table.
#' @author David L Miller
#' @export
unflatten <- function(data){
## construct region table
region.table <- unique(data[,c("Region.Label", "Area")])
# make sure that the region areas are consistent -- the above can
# lead to duplicate labels if the areas are not the same for a given
# region label
if(nrow(region.table) != length(unique(data$Region.Label))){
stop("Region areas are not consistent.")
rownames(region.table) <- 1:nrow(region.table)
# drop Area column
data <- data[,!c(colnames(data) %in% "Area")]
## construct sample table
sample.table <- unique(data[,c("Sample.Label", "Region.Label", "Effort")])
# possible that Effort is not the same for a given
# Sample.Label+Region.Label -- this is BAD.
stop("A sample has a non-unique \"Effort\", check data!")
rownames(sample.table) <- 1:nrow(sample.table)
# drop Effort column
data <- data[,!c(colnames(data) %in% "Effort")]
## construct obs
obs.table <- unique(data[,c("object", "Region.Label", "Sample.Label")])
rownames(obs.table) <- 1:nrow(obs.table)
# drop Region and Sample label columns
# actually don't do this because then we can't use subset= in dht
#data <- data[,!c(colnames(data) %in% c("Region.Label","Sample.Label"))]
rownames(data) <- 1:nrow(data)
# remove the NA rows
data <- data[!$distance),]
return(list(data=data, sample.table=sample.table, region.table=region.table,
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